Encyclopedia of Machine Learning

2010 Edition
| Editors: Claude Sammut, Geoffrey I. Webb

Greedy Search

  • Claude Sammut
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-30164-8_353

At each step in its search, a greedy algorithm makes the best decision it can at the time and continues without backtracking. For example, an algorithm may perform a  general-to-specific search and at each step, commits itself to the specialization that best fits that training data, so far. It continues without backtracking to change any of its decisions. Greedy algorithms are used in many machine-learning algorithms, including decision tree learning (Breiman, Friedman, Olshen, & Stone, 1984; Quinlan, 1993) and  rule learning algorithms, such as sequential covering.

Cross References


  1. Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees. Belmont, CA: Wadsworth International Group.MATHGoogle Scholar
  2. Quinlan, J. R. (1993). C4.5: Programs for machine learning. San Mateo, CA: Morgan Kaufmann.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Claude Sammut
    • 1
  1. 1.University of New South WalesSydneyAustralia